Causation and correlation
After learning how to describe a data set, the next step for data scientists is to start exploring the data to identify the possible interactions amongst the variables. The video covered the definitions of causation and correlations and discussed the difference between both of them.
As a data scientist, it is important to ensure that the insights and conclusions you draw from your data are sound while performing your statistical data analysis. A sound understanding of the difference between causation and correlation will help you make sure that you do not associate a causal relationship between variables that are merely correlated, which would lead to inaccurate conclusions.
Next, you will attempt a quiz to assess your knowledge about measures of spread.
Introduction to Data Science for Business
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